AI strategy and roadmap ownership
Setting the direction for where AI is adopted, prioritising use cases against risk and value, and owning whether the roadmap actually moves quarter to quarter.
Governance / Artificial Intelligence
Chief AI Officer as a Service in Malaysia
Most organisations using AI have nobody whose job it is to own that decision. CAIO as a Service gives you a named senior leader who sets the AI strategy, keeps the inventory and risk tiering current, reports to your board and makes the calls your product, data and IT teams should not have to make alone. Delivered on-site, hybrid or fully virtual, whichever suits how your team works.
Overview
Chief AI Officer as a Service (CAIO)
What it is
CAIO as a Service puts an experienced AI governance leader on a retainer, typically two to five days a month, performing the ongoing part of the Chief AI Officer role for organisations that use AI but have no one senior accountable for it. It is the retainer that runs the programme after it is built, in the same way CISO as a Service runs security after a risk assessment, or Compliance Officer as a Service runs AML/CFT after the policy is written.
Why organisations need it
Most Malaysian organisations underestimate how much AI they already run, because much of it sits inside vendor tools rather than anything built in house. JPDP's guideline on automated decision-making and profiling now brings a meaningful share of that under the PDPA, boards are starting to ask what their AI exposure is, and enterprise clients send AI governance questions alongside the usual security questionnaire. None of this is answerable by whoever happens to be closest to the AI project, and none of it is something a one-off report resolves permanently, because the inventory and the risk tiering go stale the moment a new tool is adopted.
Key features
What the engagement covers
The retainer is shaped around what your organisation runs today. These are the components most engagements include.
AI inventory and risk tiering, kept current
Maintaining the register of AI in use, including inside vendor platforms and staff tools, and re-tiering it as new tools are adopted rather than leaving the inventory to age.
ADMP and PDPA alignment
Keeping notice wording, consent points and DPIA triggers current against JPDP's guideline on automated decision-making and profiling as the AI estate changes.
Vendor AI oversight
Due diligence on new AI tools before they are adopted, ongoing monitoring of the ones already in use, and the contract clauses that matter when the vendor changes its model.
Board and management reporting
Regular reporting on AI use, risk position and incidents, written for directors rather than for a data science team.
Policy, generative AI rules and ISO/IEC 42001 ownership
Owning the AI policy and the staff rules for tools such as ChatGPT, and where certification is the goal, owning the management system between audits rather than only preparing for the first one.
Business value
What the business gets out of it
Somebody senior owns AI, not just IT or data science
The most common failure is not a bad AI decision, it is no one accountable for the AI decisions already being made. A named owner with a board reporting line changes that.
The inventory stays current
A one-off AI inventory is accurate for about as long as it takes someone to adopt a new tool. A retainer means it gets maintained, not just produced once.
PDPA and board questions have answers
When a customer asks why an automated decision was made, or a director asks what the AI exposure is, the notice, the DPIA and the register are ready rather than needing to be reconstructed.
Vendor AI gets the same scrutiny as your own
Most of the real exposure sits inside bought-in tools. Ongoing vendor oversight catches changes a one-off assessment would miss entirely.
One programme, not a new project every time something changes
AI adoption moves faster than annual review cycles. A retainer absorbs that pace instead of triggering a fresh engagement every time.
Training alongside the engagement
Orbix runs AI governance, ADMP and ISO/IEC 42001 courses. Where your team needs to carry parts of the programme, the training component is HRD Corp claimable.
How it works
How the engagement runs
01
Month 1: Baseline
Your CAIO reviews what AI is already running, including inside vendor tools and staff workflows, and talks to product, data, IT and the business to confirm the inventory.
02
Month 2: Tiering and gaps
Each use tiered by risk, assessed against the ADMP guideline and any sector framework, and the governance gaps identified.
03
Month 3: Governance in place
Policy, approval route, generative AI rules and the first board or management paper delivered. From here the work becomes maintenance and execution.
04
Ongoing: Monthly delivery
Scheduled days each month on roadmap work, vendor reviews, new tool approvals and advisory, with direct access between scheduled days for questions that cannot wait.
05
Quarterly: Board reporting and review
A board or management paper each quarter on AI risk position, new uses added, and what changed since the last one.
06
Annually: Reassessment and reset
A full re-tiering of the inventory against the baseline and a refreshed roadmap for the year ahead.
Deliverables
What you receive
AI strategy and roadmap
A living plan for where AI is adopted, reviewed and reissued quarterly.
Maintained AI inventory and risk tiering
Every AI use in scope, re-tiered as the estate changes, not produced once and left to age.
ADMP and PDPA alignment pack
Notice wording, consent points and DPIA triggers kept current against the ADMP guideline.
Vendor AI due diligence and monitoring
Assessments for new tools before adoption and ongoing checks on the ones already running.
Board and management reports
Regular papers on AI risk position, movement and decisions required, written for directors.
AI policy and governance model
Policy, accountability, approval route and generative AI rules, owned and kept current.
Who it is for
Who this is built for
Industries
Company sizes
Departments
Why Orbix
Why organisations choose Orbix
A governance approach, not a tool sale
We do not resell products, so nothing here is shaped by a vendor margin. The recommendation is whatever your risk and your budget actually justify, including telling you that you do not need the engagement yet.
Recommendations you can actually implement
Findings come with a sequence, an owner and a realistic effort estimate, sized to the team you have rather than the team a framework assumes. A report that cannot be acted on is an expense, not a control.
Consultants who have sat on your side of the table
Our people have carried the obligation internally, not only audited it. That shows up in what we consider proportionate, and in how much documentation we think you genuinely need.
Built for the Malaysian operating context
Work is grounded in Malaysian law and regulator expectation, from the PDPA and the Cyber Security Act 2024 to Bursa, BNM and SC requirements, rather than translated from a European or American template.
HRD Corp expertise where it applies
Where an engagement includes training, the training component is structured to be HRD Corp SBL-Khas claimable, which changes what the programme costs you in practice.
Questions
Questions we get asked
What is CAIO as a Service?
CAIO as a Service (Chief AI Officer as a Service) is an outsourced retainer where a named senior leader owns your AI strategy, risk tiering and board reporting on an ongoing basis, instead of a full-time hire. Delivery is on-site, hybrid or fully virtual, based on what your team needs.
How is this different from AI Governance Advisory?
AI Governance Advisory is the project: it builds the inventory, tiers the risk and designs the governance programme over a fixed engagement. CAIO as a Service is the retainer that owns and runs that programme afterwards, the way a CISO retainer follows a cybersecurity risk assessment. Many clients start with the advisory project and move to the retainer once the governance exists and someone needs to own it.
Is this delivered virtually, or on-site?
Whichever suits how your team works. We agree the mix up front: fully virtual, on-site for fixed days a month if board papers or sensitive vendor reviews need someone in the room, or a hybrid of both. Most clients settle on hybrid.
Is there a Chief AI Officer law in Malaysia?
No. There is no legal requirement to appoint a Chief AI Officer, and no standalone AI Act in force. What applies is the PDPA wherever AI uses personal data, including JPDP's guideline on automated decision-making and profiling, plus sector guidance such as the AICB framework for banks. The retainer exists to carry those obligations even though the title itself is not mandated.
How many days a month do we need?
Two to three days a month suits most organisations with AI inside a handful of vendor tools. Four to five suits organisations building AI in house or operating in a regulated sector. We start at the lower end and adjust once the real workload is visible.
Is it the same person every month?
Yes. A named consultant who learns your AI estate, your industry and your people, and is accountable for the roadmap. We name a backup for continuity during leave.
Can the CAIO also be our AI Governance Advisory consultant?
Often the same practice provides both, which avoids re-explaining the AI estate to a second team, but the retainer and the project are scoped and quoted separately.
Do you resell AI products or platforms?
No. We do not resell AI tools, models or platforms, so a CAIO recommendation is never shaped by a vendor margin. We will tell you which category of control or tool you need and leave selection and procurement to you.